It really depends upon the organization — both the specific role of the data scientist and the way in which machine learning is applied. In some organizations,

It really depends upon the organization — both the specific role of the data scientist and the way in which machine learning is applied. In some organizations, "data scientist" is the modern name for a business analyst and the responsibilities largely involve basic data sanitization and analysis, streamlining processes that were manual and tedious in previous eras. In other organizations, people with advanced mathematics skills find ways to apply mathematics and machine learning to gain a marginal advantage over competitors or to deliver something novel to the market. This latter case does indeed require a deep understanding of mathematics. Using off-the-shelf implementations of ML algos might seem like it obviates the math skills, but problem definition, algorithm selection and feature engineering are difficult for laymen to do well, and can insidiously poison the validity or efficacy of the results if done poorly.